A case study of refactoring large-scale industrial systems to efficiently improve source code quality

Szőke, Gábor, Nagy, Csaba, Ferenc, Rudolf, Gyimóthy, Tibor: A case study of refactoring large-scale industrial systems to efficiently improve source code quality.
LECTURE NOTES IN ARTIFICIAL INTELLIGENCE, 8583 (PART 5). pp. 524-540. ISSN 0302-9743 (2014)

[img]
Preview
Text
Szoke_ICCSA2014_u.pdf - Submitted Version

Download (759kB) | Preview
[img]
Preview
Text
ICCSA_2014_cimlap_tartalom.pdf - Published Version

Download (583kB) | Preview
Item Type: Article
Journal or Publication Title: LECTURE NOTES IN ARTIFICIAL INTELLIGENCE
Date: 2014
Volume: 8583
Number: PART 5
Page Range: pp. 524-540
ISSN: 0302-9743
Publisher: Springer Verlag
Faculty: Faculty of Science and Informatics
Institution: Szegedi Tudományegyetem
SWORD language: angol
MTMT id: 2853688
DOI id: https://doi.org/10.1007/978-3-319-09156-3_37
Date Deposited: 2017. May. 11. 23:24
Last Modified: 2019. Jun. 13. 10:36
URI: http://publicatio.bibl.u-szeged.hu/id/eprint/8996

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year